Last updated 27/07/2021
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, which combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases.
Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups.
Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 128TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones (AZs).
An Amazon Aurora DB cluster consists of one or more DB instances and a cluster volume that manages the data for those DB instances. An Aurora cluster volume is a virtual database storage volume that spans multiple Availability Zones, with each Availability Zone having a copy of the DB cluster data. Two types of DB instances make up an Aurora DB cluster:
The following diagram illustrates the relationship between the cluster volume, the primary DB instance, and Aurora Replicas in an Aurora DB cluster.
The preceding information applies to all the Aurora clusters that use single-master replication. These include provisioned clusters, parallel query clusters, global database clusters, serverless clusters, and all MySQL 5.7-compatible and PostgreSQL-compatible clusters.
Aurora clusters that use multi-master replication have a different arrangement of read/write and read-only DB instances. All DB instances in a multi-master cluster can perform write operations. There isn't a single DB instance that performs all the write operations, and there aren't any read-only DB instances. Therefore, the terms primary instance and Aurora Replica don't apply to multi-master clusters. When we discuss clusters that might use multi-master replication, we refer to writer DB instances and reader DB instances.
The Aurora cluster illustrates the separation of compute capacity and storage. For example, an Aurora configuration with only a single DB instance is still a cluster, because the underlying storage volume involves multiple storage nodes distributed across multiple Availability Zones (AZs).
Get 5X the throughput of standard MySQL and 3X the throughput of standard PostgreSQL. This performance is on par with commercial databases, at 1/10th the cost. You can easily scale your database deployment up and down from smaller to larger instance types as your needs change, or let Aurora Serverless handle scaling automatically for you. To scale read capacity and performance, you can add up to 15 low latency read replicas across three Availability Zones. Amazon Aurora automatically grows storage as needed, up to 128TB per database instance.
Amazon Aurora is designed to offer greater than 99.99% availability, replicating 6 copies of your data across 3 Availability Zones and backing up your data continuously to Amazon S3. It transparently recovers from physical storage failures; instance failover typically takes less than 30 seconds. You can also backtrack within seconds to a previous point in time, to recover from user errors. With Global Database, a single Aurora database can span multiple AWS regions to enable fast local reads and quick disaster recovery.
Amazon Aurora provides multiple levels of security for your database. These include network isolation using Amazon VPC, encryption at rest using keys you create and control through AWS Key Management Service (KMS), and encryption of data in transit using SSL. On an encrypted Amazon Aurora instance, data in the underlying storage is encrypted, as are the automated backups, snapshots, and replicas in the same cluster.
The Amazon Aurora database engine is fully compatible with existing MySQL and PostgreSQL open source databases, and adds compatibility for new releases regularly. This means you can easily migrate MySQL or PostgreSQL databases to Aurora using standard MySQL or PostgreSQL import/export tools or snapshots. It also means the code, applications, drivers, and tools you already use with your existing databases can be used with Amazon Aurora with little or no change.
Amazon Aurora is fully managed by Amazon Relational Database Service (RDS). You no longer need to worry about database management tasks such as hardware provisioning, software patching, setup, configuration, or backups. Aurora automatically and continuously monitors and backs up your database to Amazon S3, enabling granular point-in-time recovery. You can monitor database performance using Amazon CloudWatch, Enhanced Monitoring, or Performance Insights, an easy-to-use tool that helps you quickly detect performance problems.
MySQL and PostgreSQL compatibility make Amazon Aurora a compelling target for database migrations to the cloud. If you're migrating from MySQL or PostgreSQL, see our migration documentation for a list of tools and options. To migrate from commercial database engines, you can use the AWS Database Migration Service for a secure migration with minimal downtime.
Amazon Aurora is a great option for any enterprise application that can use a relational database. Compared to commercial databases, Amazon Aurora can help cut down your database costs by 90% or more while improving the reliability and availability of the database. Amazon Aurora being a fully managed service helps you save time by automating time-consuming tasks such as provisioning, patching, backup, recovery, failure detection, and repair.
SaaS applications often use architectures that are multi-tenant, which requires a great deal of flexibility in instance and storage scaling along with high performance and reliability. Amazon Aurora provides all of these features in a managed database offering, helping SaaS companies focus on building high-quality applications without worrying about the underlying database that powers the application
Web and mobile games that are built to operate at a very large scale need a database with high throughput, massive storage scalability, and high availability. Amazon Aurora fulfills the needs of such highly demanding applications with enough room for future growth. Since Amazon Aurora does not have any licensing constraints, it perfectly fits the variable usage pattern of these applications.
Samsung moved over a billion users across three continents from Oracle to Amazon Aurora, improving latency and scalability while lowering monthly costs.
DoorDash uses Amazon Aurora to help it make over 800,000 deliveries a day, managing billions of rows and nearly 10 TB of data in a single Aurora cluster.
Amazon Aurora enables Pokémon to support 300+ million users, including 300 login requests per second, while automating administrative tasks.
Dow Jones migrated its market data service from an on-premises database to Amazon Aurora ahead of schedule and with no disruption to service.
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